Senior Data Engineer
Job Summary
Job Description
N-iX is seeking a Senior Data Engineer in Kyiv with expertise in PySpark to design, develop, and optimize large-scale data pipelines. Responsibilities include collaborating with stakeholders to define data requirements, ensuring efficient data processing and integration, optimizing workflows for performance and reliability, maintaining data integrity and security, and developing technical documentation. Experience with Palantir Foundry is a significant plus. The role involves working with big data technologies (Hadoop, Databricks) and cloud platforms (AWS, Azure, GCP).
Must have:
- 5+ years Data Engineering experience with PySpark focus
- Strong Apache Spark, distributed computing, performance tuning knowledge
- SQL, data modeling, ETL process expertise
- Big data technologies (Hadoop, Databricks etc.) experience
- Data requirements gathering and refinement
Good to have:
- Palantir Foundry experience
- Streaming technologies (Kafka)
- Containerization and orchestration (Docker, Kubernetes, Airflow)
- Cloud platform experience (AWS, Azure, GCP)
- CI/CD, Git, DevOps practices
Perks:
- Flexible working format (remote, office, hybrid)
- Competitive salary and compensation package
- Personalized career growth
- Professional development tools
- Active tech communities
- Education reimbursement
- Corporate events and team buildings
12 skills required
Job Details
N-iX is looking for a Senior Data Engineer with strong expertise in PySpark to join our team in Kyiv. In this role, you will design, develop, and optimize large-scale data pipelines, ensuring efficient data processing and integration. You will also collaborate closely with business stakeholders to gather and refine data requirements, ensuring solutions align with business needs. Experience with Palantir Foundry is a huge plus.
Responsibilities:
- Design and implement scalable ETL/ELT pipelines using PySpark.
- Work closely with product owners, and different stakeholders to gather, analyze, and translate data requirements into technical solutions.
- Optimize data processing workflows for performance and reliability.
- Ensure data integrity, governance, and security best practices.
- Develop and maintain technical documentation for data pipelines and transformations.
- Troubleshoot and optimize Spark jobs to improve efficiency.
- Work with cloud-based or on-premises big data technologies.
Requirements:
- 5+ years of experience in data engineering, with a focus on PySpark.
- Strong knowledge of Apache Spark, distributed computing, and performance tuning.
- Experience gathering and refining business and technical data requirements.
- Hands-on experience with SQL, data modeling, and ETL processes.
- Proficiency in working with big data technologies (Hadoop, Databricks, etc.).
- Experience with cloud platforms (AWS, Azure, GCP) is a plus.
- Knowledge of CI/CD, version control (Git), and DevOps practices.
- Excellent problem-solving and communication skills.
Nice to have:
- Experience with Palantir Foundry.
- Familiarity with streaming technologies (Kafka).
- Exposure to containerization and orchestration (Docker, Kubernetes, Airflow).
We offer:
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
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